Tracking active galactic nuclei feedback from parsec to kiloparsec scales

In force date
Call year
2022
Investigator
Cristina
Ramos Almeida
Amount granted to the IAC Consortium
156.875,00 €
Description

Active galactic nuclei (AGN) feedback is the effect that nuclear activity produces in the interstellar and circumgalactic medium (ISM and CGM) of galaxies. Different modes of AGN feedback, which can be broadly divided into radiative/quasar and kinetic/radio, are now considered key processes in the evolution of massive galaxies by regulating black hole and galaxy growth. Indeed, a wealth of observational evidence demonstrates that feedback from supermassive black holes (SMBHs) impacts the galaxies and the haloes they inhabit on a wide range of scales: from the central parsecs to hundreds of kiloparsecs. What we are still far from understanding is how AGN feedback couples with the host galaxy, which is what ultimately determines its efficiency. The goal of AGNFEED is to answer this question by focusing on the nuclear regions that are being directly affected by the current episode of nuclear activity (<10 Mry).

 We aim at tracking the multi-phase AGN-driven winds from the central parsecs (torus-scales) to the inner 1-3 kpc of nearby active galaxies. Then, we will quantify their impact on host galaxy properties/features having the same dynamical timescale (recent star formation and nuclear molecular gas distributions). To do so, the project requires the use of high angular resolution cutting-edge observations (e.g., GTC/EMIR and MEGARA, JWST and ALMA) of different samples of AGN covering a wide luminosity range. Finally, we will compare these observations with tailored hydrodynamical simulations of gas at different densities, developed by our collaborators.

 This is a project aimed at promoting the generation and advancement of knowledge that builds on our on-going international collaborations: the Quasar Feedback (QSOFEED) project (PI: C. Ramos Almeida), the Big Data applications for Black hole Evolution Studies (BID4BESt) H2020 Innovative Training Network (PI: F. Sharkar; University of Southampton, UK), and the Galactic Activity, Torus and Outflow Survey (GATOS, PI: A. Alonso Herrero, CAB, Spain).

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Type of funding
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AEI
EU_COFINANCIADO POR LA UNIÓN EUROPEA
MICIU